What is a Voicebot?

Advances in Natural Language Understanding (NLU) are leading to significant changes in call center technology. For example, text chats with live agents are making way for automated chats, via in a "chatbot", which is a form of artificial intelligence (AI) that enables the customer to experience a natural interaction, even though they are chatting with a computer.

More recently, a similar transition is occurring with the use of automated voice in the call center, ushering in a next generation of IVR that is AI-enabled. This technology is being referred to as "voicebots", but may also be called "next generation IVR" or "NLU IVR" or "virtual agents".

The concept of a voicebot is not new. Starting in the early 1990s, several companies attempted to deliver a natural language type dialog; however, they suffered from extremely high cost and the inability to be open-ended. Fortunately, the latest advances in AI and deep learning promise to make this generation of voicebots vastly better than previous attempts, and able to be delivered cost-effectively.

How Do You Authenticate with a Voicebot?

Security and privacy policies require a reliable means to authenticate callers to the contact center. Live agents use Knowledge-Based Authentication (KBA), a process where agents ask the callers questions that presumably are only known by the callers. And, active forms of voice biometrics performed in the IVR, such as RandomPIN™ and Static Passphrase, help to hand-off authenticated users to the live agent. However, voicebots can be used to provide even more automation throughout the interaction with the caller, thus saving money and reducing customer wait times.

What's the best means to authenticate a fully automated call? Is voice-based KBA the right approach? Some forms of KBA that rely on dates and numbers should work fine. Other KBA options won't work well, especially when needing to process odd spellings of names and locations. Also, KBA is a single factor and is less secure. Fortunately, there is a better solution to authenticating voicebot interactions: voice biometrics.

Voice Biometrics and Voicebots

One obvious approach to automate authentication is to implement an active voice biometric, such as RandomPIN™, just like in a traditional IVR in front of a call center. Active voice biometrics adds an extra layer of security. It is faster than a typical agent KBA interrogation. But on the other hand, it requires explicit enrollment and verification by the caller.

Another less obvious but clever approach is to leverage passive voice biometrics, such as VBG's NaturalSpeech™ technology with a voicebot. A voicebot attempts to engage the caller in more of a natural way. If you capture natural, conversational utterances from the caller as the caller interacts with the voicebot, you now have the makings for a NaturalSpeech voiceprint. By using VBG's model update capability, you can add new utterances, whether on the same call or subsequent calls, to your voiceprint until you have created a sufficiently robust voiceprint. Then on a future interaction, you use one or more utterances for verification.

Several critical success factors exist for a real-world deployment:

You must be able to update the voiceprint with additional speech samples over time and not rely on a single submission to create or verify a voiceprint

You must keep track of whether you have collected enough speech for a robust voiceprint

You need to know whether you have accumulated enough speech for a reliable verification, as it may take more than one utterance to capture several seconds of speech

Fortunately, VBG's RESTful API gives you all this information for each user identity as you make enrollment and verification requests. You don't need to keep track on your end, simplifying your development effort. Your application can stay focused on the user dialog. And only when you have a conclusive result do you need to take action.

Benefits of Passive Authentication

No additional work by the caller; no instructions to follow or explicit enrollment

No risk to the user experience and the fear that customers will disklike the system because of extra effort or a failure to authenticate

Easy implementation within the voicebot that can be phased, first starting with a data collection before acting on the results

These advantages mean that adding passive voice biometrics to a voicebot is a no-risk proposition. If you have a voicebot and verifying your callers is important, there's every reason to begin a passive voice biometric project right away.

Regulatory Considerations

It is important to remember that speech samples, and the voiceprints that are created from them, are considered Personally Identifiable Information (PII). The same is true for fingerprint biometrics, retinal scans, and other forms of biometric technology. So remember, when using voice biometric technology, you have an obligation to inform your callers that you are recording their speech.

If you are subject to a Biometric Information Protect Act (BIPA or similar) in your state, or if you follow GDPR in the EU, you have additional responsibilities. For instance, you must obtain written consent to collect their biometric information, must clearly describe why you are collecting this data, how long you will keep it, etc. And, you may be required to provide copies of all personal data you collect from your end users back to them.

VBG strongly recommends that you consult with a legal team who is well-versed in these matters BEFORE embarking on any project using voice biometrics.

Summary

The use of voicebot-based technologies is gaining momentum and will likely become the de-facto standard for IVR in the near future. At the same time, authenticating callers is more important than ever, and voicebots needs a reliable authentication method. Voice Biometrics Group offers a highly reliable and easy to implement solutions for both active and passive authentication in a voicebot.